{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Vosk Training",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vdqvrs5TYr2Y",
        "outputId": "206d38b4-0819-488a-eb05-53a80d766bc5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "--2022-08-17 10:53:18--  https://alphacephei.com/vosk-colab/kaldi.tar.gz\n",
            "Resolving alphacephei.com (alphacephei.com)... 188.40.21.16, 2a01:4f8:13a:279f::2\n",
            "Connecting to alphacephei.com (alphacephei.com)|188.40.21.16|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 809174554 (772M) [application/octet-stream]\n",
            "Saving to: ‘kaldi.tar.gz’\n",
            "\n",
            "kaldi.tar.gz        100%[===================>] 771.69M   108MB/s    in 7.2s    \n",
            "\n",
            "2022-08-17 10:53:25 (106 MB/s) - ‘kaldi.tar.gz’ saved [809174554/809174554]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!wget -c https://alphacephei.com/vosk-colab/kaldi.tar.gz\n",
        "!tar xzf kaldi.tar.gz"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content\n",
        "!rm -rf vosk-api\n",
        "!git clone https://github.com/alphacep/vosk-api"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OfUtX42VZ1zl",
        "outputId": "0cbed826-bac2-4e15-dfa2-2a101b3562dd"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "Cloning into 'vosk-api'...\n",
            "remote: Enumerating objects: 3259, done.\u001b[K\n",
            "remote: Counting objects: 100% (124/124), done.\u001b[K\n",
            "remote: Compressing objects: 100% (92/92), done.\u001b[K\n",
            "remote: Total 3259 (delta 45), reused 92 (delta 28), pack-reused 3135\u001b[K\n",
            "Receiving objects: 100% (3259/3259), 1.07 MiB | 8.46 MiB/s, done.\n",
            "Resolving deltas: 100% (1847/1847), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!rm -rf /content/kaldi/egs/ac/training\n",
        "!cp -r /content/vosk-api/training /content/kaldi/egs/ac"
      ],
      "metadata": {
        "id": "bwdTkMVpZ4Pb"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!apt install flac"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xvC_AENtasCF",
        "outputId": "d0740818-836c-40d4-9e44-3f966e83128c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-460\n",
            "Use 'apt autoremove' to remove it.\n",
            "The following NEW packages will be installed:\n",
            "  flac\n",
            "0 upgraded, 1 newly installed, 0 to remove and 20 not upgraded.\n",
            "Need to get 144 kB of archives.\n",
            "After this operation, 438 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 flac amd64 1.3.2-1 [144 kB]\n",
            "Fetched 144 kB in 0s (294 kB/s)\n",
            "Selecting previously unselected package flac.\n",
            "(Reading database ... 155676 files and directories currently installed.)\n",
            "Preparing to unpack .../flac_1.3.2-1_amd64.deb ...\n",
            "Unpacking flac (1.3.2-1) ...\n",
            "Setting up flac (1.3.2-1) ...\n",
            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/kaldi/egs/ac/training\n",
        "!rm -rf exp\n",
        "!sed -i 's:--nj 10:--nj 2:g' run.sh\n",
        "!cat run.sh\n",
        "!bash run.sh --stop-stage 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lv1cbjZuaE6O",
        "outputId": "13cb7312-97d6-42ec-910a-8095ba1eb967"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/kaldi/egs/ac/training\n",
            "#!/usr/bin/env bash\n",
            "\n",
            ". ./cmd.sh\n",
            ". ./path.sh\n",
            "\n",
            "stage=-1\n",
            "stop_stage=100\n",
            "\n",
            ". utils/parse_options.sh\n",
            "\n",
            "# Data preparation\n",
            "if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then\n",
            "  data_url=www.openslr.org/resources/31\n",
            "  lm_url=www.openslr.org/resources/11\n",
            "  database=corpus\n",
            "\n",
            "  mkdir -p $database\n",
            "  for part in dev-clean-2 train-clean-5; do\n",
            "    local/download_and_untar.sh $database $data_url $part\n",
            "  done\n",
            "\n",
            "  local/download_lm.sh $lm_url $database data/local/lm\n",
            "\n",
            "  local/data_prep.sh $database/LibriSpeech/train-clean-5 data/train\n",
            "  local/data_prep.sh $database/LibriSpeech/dev-clean-2 data/test\n",
            "fi\n",
            "\n",
            "# Dictionary formatting\n",
            "if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then\n",
            "  local/prepare_dict.sh data/local/lm data/local/dict\n",
            "  utils/prepare_lang.sh data/local/dict \"<UNK>\" data/local/lang data/lang\n",
            "fi\n",
            "\n",
            "# Extract MFCC features\n",
            "if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then\n",
            "  for task in train; do\n",
            "    steps/make_mfcc.sh --cmd \"$train_cmd\" --nj 2 data/$task exp/make_mfcc/$task $mfcc\n",
            "    steps/compute_cmvn_stats.sh data/$task exp/make_mfcc/$task $mfcc\n",
            "  done\n",
            "fi\n",
            "\n",
            "# Train GMM models\n",
            "if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then\n",
            "  steps/train_mono.sh --nj 2 --cmd \"$train_cmd\" \\\n",
            "    data/train data/lang exp/mono\n",
            "\n",
            "  steps/align_si.sh  --nj 2 --cmd \"$train_cmd\" \\\n",
            "    data/train data/lang exp/mono exp/mono_ali\n",
            "\n",
            "  steps/train_lda_mllt.sh  --cmd \"$train_cmd\" \\\n",
            "    2000 10000 data/train data/lang exp/mono_ali exp/tri1\n",
            "\n",
            "  steps/align_si.sh --nj 2 --cmd \"$train_cmd\" \\\n",
            "    data/train data/lang exp/tri1 exp/tri1_ali\n",
            "\n",
            "  steps/train_lda_mllt.sh --cmd \"$train_cmd\" \\\n",
            "    2500 15000 data/train data/lang exp/tri1_ali exp/tri2\n",
            "\n",
            "  steps/align_si.sh  --nj 2 --cmd \"$train_cmd\" \\\n",
            "    data/train data/lang exp/tri2 exp/tri2_ali\n",
            "\n",
            "  steps/train_lda_mllt.sh --cmd \"$train_cmd\" \\\n",
            "    2500 20000 data/train data/lang exp/tri2_ali exp/tri3\n",
            "\n",
            "  steps/align_si.sh  --nj 2 --cmd \"$train_cmd\" \\\n",
            "    data/train data/lang exp/tri3 exp/tri3_ali\n",
            "fi\n",
            "\n",
            "# Train TDNN model\n",
            "if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then\n",
            "  local/chain/run_tdnn.sh\n",
            "fi\n",
            "\n",
            "# Decode\n",
            "if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then\n",
            "\n",
            "  utils/format_lm.sh data/lang data/local/lm/lm_tgsmall.arpa.gz data/local/dict/lexicon.txt data/lang_test\n",
            "  utils/mkgraph.sh --self-loop-scale 1.0 data/lang_test exp/chain/tdnn exp/chain/tdnn/graph\n",
            "  utils/build_const_arpa_lm.sh data/local/lm/lm_tgmed.arpa.gz \\\n",
            "    data/lang data/lang_test_rescore\n",
            "\n",
            "  for task in test; do\n",
            "\n",
            "    steps/make_mfcc.sh --cmd \"$train_cmd\" --nj 2 data/$task exp/make_mfcc/$task $mfcc\n",
            "    steps/compute_cmvn_stats.sh data/$task exp/make_mfcc/$task $mfcc\n",
            "\n",
            "    steps/online/nnet2/extract_ivectors_online.sh --nj 2 \\\n",
            "        data/${task} exp/chain/extractor \\\n",
            "        exp/chain/ivectors_${task}\n",
            "\n",
            "    steps/nnet3/decode.sh --cmd $decode_cmd --num-threads 10 --nj 1 \\\n",
            "         --beam 13.0 --max-active 7000 --lattice-beam 4.0 \\\n",
            "         --online-ivector-dir exp/chain/ivectors_${task} \\\n",
            "         --acwt 1.0 --post-decode-acwt 10.0 \\\n",
            "         exp/chain/tdnn/graph data/${task} exp/chain/tdnn/decode_${task}\n",
            "\n",
            "    steps/lmrescore_const_arpa.sh data/lang_test data/lang_test_rescore \\\n",
            "        data/${task} exp/chain/tdnn/decode_${task} exp/chain/tdnn/decode_${task}_rescore\n",
            "  done\n",
            "\n",
            "  bash RESULTS\n",
            "fi\n",
            "local/download_and_untar.sh: downloading data from www.openslr.org/resources/31/dev-clean-2.tar.gz.  This may take some time, please be patient.\n",
            "--2022-08-17 12:36:38--  http://www.openslr.org/resources/31/dev-clean-2.tar.gz\n",
            "Resolving www.openslr.org (www.openslr.org)... 46.101.158.64\n",
            "Connecting to www.openslr.org (www.openslr.org)|46.101.158.64|:80... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://us.openslr.org/resources/31/dev-clean-2.tar.gz [following]\n",
            "--2022-08-17 12:36:38--  https://us.openslr.org/resources/31/dev-clean-2.tar.gz\n",
            "Resolving us.openslr.org (us.openslr.org)... 46.101.158.64\n",
            "Connecting to us.openslr.org (us.openslr.org)|46.101.158.64|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 126046265 (120M) [application/x-gzip]\n",
            "Saving to: 'dev-clean-2.tar.gz'\n",
            "\n",
            "dev-clean-2.tar.gz  100%[===================>] 120.21M   106MB/s    in 1.1s    \n",
            "\n",
            "2022-08-17 12:36:39 (106 MB/s) - 'dev-clean-2.tar.gz' saved [126046265/126046265]\n",
            "\n",
            "/content/kaldi/egs/ac/training\n",
            "LibriSpeech/dev-clean-2/\n",
            "LibriSpeech/dev-clean-2/5694/\n",
            "LibriSpeech/dev-clean-2/5694/64038/\n",
            "LibriSpeech/dev-clean-2/5694/64038/5694-64038.trans.txt\n",
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            "LibriSpeech/dev-clean-2/3000/\n",
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            "LibriSpeech/dev-clean-2/7850/\n",
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            "LibriSpeech/dev-clean-2/7850/286674/7850-286674.trans.txt\n",
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            "LibriSpeech/dev-clean-2/7850/281318/\n",
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            "\n",
            "utils/validate_data_dir.sh: Successfully validated data-directory data/train\n",
            "local/data_prep.sh: successfully prepared data in data/train\n",
            "utils/validate_data_dir.sh: Successfully validated data-directory data/test\n",
            "local/data_prep.sh: successfully prepared data in data/test\n",
            "Preparing phone lists and lexicon\n",
            "utils/prepare_lang.sh data/local/dict <UNK> data/local/lang data/lang\n",
            "Checking data/local/dict/silence_phones.txt ...\n",
            "--> reading data/local/dict/silence_phones.txt\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/local/dict/silence_phones.txt is OK\n",
            "\n",
            "Checking data/local/dict/optional_silence.txt ...\n",
            "--> reading data/local/dict/optional_silence.txt\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/local/dict/optional_silence.txt is OK\n",
            "\n",
            "Checking data/local/dict/nonsilence_phones.txt ...\n",
            "--> reading data/local/dict/nonsilence_phones.txt\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/local/dict/nonsilence_phones.txt is OK\n",
            "\n",
            "Checking disjoint: silence_phones.txt, nonsilence_phones.txt\n",
            "--> disjoint property is OK.\n",
            "\n",
            "Checking data/local/dict/lexicon.txt\n",
            "--> reading data/local/dict/lexicon.txt\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/local/dict/lexicon.txt is OK\n",
            "\n",
            "Checking data/local/dict/extra_questions.txt ...\n",
            "--> data/local/dict/extra_questions.txt is empty (this is OK)\n",
            "--> SUCCESS [validating dictionary directory data/local/dict]\n",
            "\n",
            "**Creating data/local/dict/lexiconp.txt from data/local/dict/lexicon.txt\n",
            "fstaddselfloops data/lang/phones/wdisambig_phones.int data/lang/phones/wdisambig_words.int \n",
            "prepare_lang.sh: validating output directory\n",
            "utils/validate_lang.pl data/lang\n",
            "Checking existence of separator file\n",
            "separator file data/lang/subword_separator.txt is empty or does not exist, deal in word case.\n",
            "Checking data/lang/phones.txt ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/lang/phones.txt is OK\n",
            "\n",
            "Checking words.txt: #0 ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> data/lang/words.txt is OK\n",
            "\n",
            "Checking disjoint: silence.txt, nonsilence.txt, disambig.txt ...\n",
            "--> silence.txt and nonsilence.txt are disjoint\n",
            "--> silence.txt and disambig.txt are disjoint\n",
            "--> disambig.txt and nonsilence.txt are disjoint\n",
            "--> disjoint property is OK\n",
            "\n",
            "Checking sumation: silence.txt, nonsilence.txt, disambig.txt ...\n",
            "--> found no unexplainable phones in phones.txt\n",
            "\n",
            "Checking data/lang/phones/context_indep.{txt, int, csl} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 10 entry/entries in data/lang/phones/context_indep.txt\n",
            "--> data/lang/phones/context_indep.int corresponds to data/lang/phones/context_indep.txt\n",
            "--> data/lang/phones/context_indep.csl corresponds to data/lang/phones/context_indep.txt\n",
            "--> data/lang/phones/context_indep.{txt, int, csl} are OK\n",
            "\n",
            "Checking data/lang/phones/nonsilence.{txt, int, csl} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 156 entry/entries in data/lang/phones/nonsilence.txt\n",
            "--> data/lang/phones/nonsilence.int corresponds to data/lang/phones/nonsilence.txt\n",
            "--> data/lang/phones/nonsilence.csl corresponds to data/lang/phones/nonsilence.txt\n",
            "--> data/lang/phones/nonsilence.{txt, int, csl} are OK\n",
            "\n",
            "Checking data/lang/phones/silence.{txt, int, csl} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 10 entry/entries in data/lang/phones/silence.txt\n",
            "--> data/lang/phones/silence.int corresponds to data/lang/phones/silence.txt\n",
            "--> data/lang/phones/silence.csl corresponds to data/lang/phones/silence.txt\n",
            "--> data/lang/phones/silence.{txt, int, csl} are OK\n",
            "\n",
            "Checking data/lang/phones/optional_silence.{txt, int, csl} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 1 entry/entries in data/lang/phones/optional_silence.txt\n",
            "--> data/lang/phones/optional_silence.int corresponds to data/lang/phones/optional_silence.txt\n",
            "--> data/lang/phones/optional_silence.csl corresponds to data/lang/phones/optional_silence.txt\n",
            "--> data/lang/phones/optional_silence.{txt, int, csl} are OK\n",
            "\n",
            "Checking data/lang/phones/disambig.{txt, int, csl} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 21 entry/entries in data/lang/phones/disambig.txt\n",
            "--> data/lang/phones/disambig.int corresponds to data/lang/phones/disambig.txt\n",
            "--> data/lang/phones/disambig.csl corresponds to data/lang/phones/disambig.txt\n",
            "--> data/lang/phones/disambig.{txt, int, csl} are OK\n",
            "\n",
            "Checking data/lang/phones/roots.{txt, int} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 41 entry/entries in data/lang/phones/roots.txt\n",
            "--> data/lang/phones/roots.int corresponds to data/lang/phones/roots.txt\n",
            "--> data/lang/phones/roots.{txt, int} are OK\n",
            "\n",
            "Checking data/lang/phones/sets.{txt, int} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 41 entry/entries in data/lang/phones/sets.txt\n",
            "--> data/lang/phones/sets.int corresponds to data/lang/phones/sets.txt\n",
            "--> data/lang/phones/sets.{txt, int} are OK\n",
            "\n",
            "Checking data/lang/phones/extra_questions.{txt, int} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 9 entry/entries in data/lang/phones/extra_questions.txt\n",
            "--> data/lang/phones/extra_questions.int corresponds to data/lang/phones/extra_questions.txt\n",
            "--> data/lang/phones/extra_questions.{txt, int} are OK\n",
            "\n",
            "Checking data/lang/phones/word_boundary.{txt, int} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 166 entry/entries in data/lang/phones/word_boundary.txt\n",
            "--> data/lang/phones/word_boundary.int corresponds to data/lang/phones/word_boundary.txt\n",
            "--> data/lang/phones/word_boundary.{txt, int} are OK\n",
            "\n",
            "Checking optional_silence.txt ...\n",
            "--> reading data/lang/phones/optional_silence.txt\n",
            "--> data/lang/phones/optional_silence.txt is OK\n",
            "\n",
            "Checking disambiguation symbols: #0 and #1\n",
            "--> data/lang/phones/disambig.txt has \"#0\" and \"#1\"\n",
            "--> data/lang/phones/disambig.txt is OK\n",
            "\n",
            "Checking topo ...\n",
            "\n",
            "Checking word_boundary.txt: silence.txt, nonsilence.txt, disambig.txt ...\n",
            "--> data/lang/phones/word_boundary.txt doesn't include disambiguation symbols\n",
            "--> data/lang/phones/word_boundary.txt is the union of nonsilence.txt and silence.txt\n",
            "--> data/lang/phones/word_boundary.txt is OK\n",
            "\n",
            "Checking word-level disambiguation symbols...\n",
            "--> data/lang/phones/wdisambig.txt exists (newer prepare_lang.sh)\n",
            "Checking word_boundary.int and disambig.int\n",
            "--> generating a 27 word/subword sequence\n",
            "--> resulting phone sequence from L.fst corresponds to the word sequence\n",
            "--> L.fst is OK\n",
            "--> generating a 73 word/subword sequence\n",
            "--> resulting phone sequence from L_disambig.fst corresponds to the word sequence\n",
            "--> L_disambig.fst is OK\n",
            "\n",
            "Checking data/lang/oov.{txt, int} ...\n",
            "--> text seems to be UTF-8 or ASCII, checking whitespaces\n",
            "--> text contains only allowed whitespaces\n",
            "--> 1 entry/entries in data/lang/oov.txt\n",
            "--> data/lang/oov.int corresponds to data/lang/oov.txt\n",
            "--> data/lang/oov.{txt, int} are OK\n",
            "\n",
            "--> data/lang/L.fst is olabel sorted\n",
            "--> data/lang/L_disambig.fst is olabel sorted\n",
            "--> SUCCESS [validating lang directory data/lang]\n",
            "steps/make_mfcc.sh --cmd run.pl --nj 2 data/train exp/make_mfcc/train\n",
            "utils/validate_data_dir.sh: Successfully validated data-directory data/train\n",
            "steps/make_mfcc.sh: [info]: no segments file exists: assuming wav.scp indexed by utterance.\n",
            "steps/make_mfcc.sh: Succeeded creating MFCC features for train\n",
            "steps/compute_cmvn_stats.sh data/train exp/make_mfcc/train\n",
            "Succeeded creating CMVN stats for train\n",
            "steps/train_mono.sh --nj 2 --cmd run.pl data/train data/lang exp/mono\n",
            "steps/train_mono.sh: Initializing monophone system.\n",
            "steps/train_mono.sh: Compiling training graphs\n",
            "steps/train_mono.sh: Aligning data equally (pass 0)\n",
            "steps/train_mono.sh: Pass 1\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 2\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 3\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 4\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 5\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 6\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 7\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 8\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 9\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 10\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 11\n",
            "steps/train_mono.sh: Pass 12\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 13\n",
            "steps/train_mono.sh: Pass 14\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 15\n",
            "steps/train_mono.sh: Pass 16\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 17\n",
            "steps/train_mono.sh: Pass 18\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 19\n",
            "steps/train_mono.sh: Pass 20\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 21\n",
            "steps/train_mono.sh: Pass 22\n",
            "steps/train_mono.sh: Pass 23\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 24\n",
            "steps/train_mono.sh: Pass 25\n",
            "steps/train_mono.sh: Pass 26\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 27\n",
            "steps/train_mono.sh: Pass 28\n",
            "steps/train_mono.sh: Pass 29\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 30\n",
            "steps/train_mono.sh: Pass 31\n",
            "steps/train_mono.sh: Pass 32\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 33\n",
            "steps/train_mono.sh: Pass 34\n",
            "steps/train_mono.sh: Pass 35\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 36\n",
            "steps/train_mono.sh: Pass 37\n",
            "steps/train_mono.sh: Pass 38\n",
            "steps/train_mono.sh: Aligning data\n",
            "steps/train_mono.sh: Pass 39\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/mono\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/mono/log/analyze_alignments.log\n",
            "896 warnings in exp/mono/log/acc.*.*.log\n",
            "7156 warnings in exp/mono/log/align.*.*.log\n",
            "exp/mono: nj=2 align prob=-247.97 over 5.21h [retry=17.3%, fail=1.6%] states=127 gauss=1000\n",
            "steps/train_mono.sh: Done training monophone system in exp/mono\n",
            "steps/align_si.sh --nj 2 --cmd run.pl data/train data/lang exp/mono exp/mono_ali\n",
            "steps/align_si.sh: feature type is delta\n",
            "steps/align_si.sh: aligning data in data/train using model from exp/mono, putting alignments in exp/mono_ali\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/mono_ali\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/mono_ali/log/analyze_alignments.log\n",
            "steps/align_si.sh: done aligning data.\n",
            "steps/train_lda_mllt.sh --cmd run.pl 2000 10000 data/train data/lang exp/mono_ali exp/tri1\n",
            "steps/train_lda_mllt.sh: Accumulating LDA statistics.\n",
            "steps/train_lda_mllt.sh: Accumulating tree stats\n",
            "steps/train_lda_mllt.sh: Getting questions for tree clustering.\n",
            "steps/train_lda_mllt.sh: Building the tree\n",
            "steps/train_lda_mllt.sh: Initializing the model\n",
            "steps/train_lda_mllt.sh: Converting alignments from exp/mono_ali to use current tree\n",
            "steps/train_lda_mllt.sh: Compiling graphs of transcripts\n",
            "Training pass 1\n",
            "Training pass 2\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 3\n",
            "Training pass 4\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 5\n",
            "Training pass 6\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 7\n",
            "Training pass 8\n",
            "Training pass 9\n",
            "Training pass 10\n",
            "Aligning data\n",
            "Training pass 11\n",
            "Training pass 12\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 13\n",
            "Training pass 14\n",
            "Training pass 15\n",
            "Training pass 16\n",
            "Training pass 17\n",
            "Training pass 18\n",
            "Training pass 19\n",
            "Training pass 20\n",
            "Aligning data\n",
            "Training pass 21\n",
            "Training pass 22\n",
            "Training pass 23\n",
            "Training pass 24\n",
            "Training pass 25\n",
            "Training pass 26\n",
            "Training pass 27\n",
            "Training pass 28\n",
            "Training pass 29\n",
            "Training pass 30\n",
            "Aligning data\n",
            "Training pass 31\n",
            "Training pass 32\n",
            "Training pass 33\n",
            "Training pass 34\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri1\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri1/log/analyze_alignments.log\n",
            "25 warnings in exp/tri1/log/lda_acc.*.log\n",
            "375 warnings in exp/tri1/log/acc.*.*.log\n",
            "1 warnings in exp/tri1/log/build_tree.log\n",
            "5 warnings in exp/tri1/log/update.*.log\n",
            "30 warnings in exp/tri1/log/init_model.log\n",
            "274 warnings in exp/tri1/log/align.*.*.log\n",
            "exp/tri1: nj=2 align prob=-46.98 over 5.29h [retry=3.0%, fail=0.3%] states=1608 gauss=10025 tree-impr=4.06 lda-sum=10.11 mllt:impr,logdet=0.91,1.33\n",
            "steps/train_lda_mllt.sh: Done training system with LDA+MLLT features in exp/tri1\n",
            "steps/align_si.sh --nj 2 --cmd run.pl data/train data/lang exp/tri1 exp/tri1_ali\n",
            "steps/align_si.sh: feature type is lda\n",
            "steps/align_si.sh: aligning data in data/train using model from exp/tri1, putting alignments in exp/tri1_ali\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri1_ali\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri1_ali/log/analyze_alignments.log\n",
            "steps/align_si.sh: done aligning data.\n",
            "steps/train_lda_mllt.sh --cmd run.pl 2500 15000 data/train data/lang exp/tri1_ali exp/tri2\n",
            "steps/train_lda_mllt.sh: Accumulating LDA statistics.\n",
            "steps/train_lda_mllt.sh: Accumulating tree stats\n",
            "steps/train_lda_mllt.sh: Getting questions for tree clustering.\n",
            "steps/train_lda_mllt.sh: Building the tree\n",
            "steps/train_lda_mllt.sh: Initializing the model\n",
            "steps/train_lda_mllt.sh: Converting alignments from exp/tri1_ali to use current tree\n",
            "steps/train_lda_mllt.sh: Compiling graphs of transcripts\n",
            "Training pass 1\n",
            "Training pass 2\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 3\n",
            "Training pass 4\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 5\n",
            "Training pass 6\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 7\n",
            "Training pass 8\n",
            "Training pass 9\n",
            "Training pass 10\n",
            "Aligning data\n",
            "Training pass 11\n",
            "Training pass 12\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 13\n",
            "Training pass 14\n",
            "Training pass 15\n",
            "Training pass 16\n",
            "Training pass 17\n",
            "Training pass 18\n",
            "Training pass 19\n",
            "Training pass 20\n",
            "Aligning data\n",
            "Training pass 21\n",
            "Training pass 22\n",
            "Training pass 23\n",
            "Training pass 24\n",
            "Training pass 25\n",
            "Training pass 26\n",
            "Training pass 27\n",
            "Training pass 28\n",
            "Training pass 29\n",
            "Training pass 30\n",
            "Aligning data\n",
            "Training pass 31\n",
            "Training pass 32\n",
            "Training pass 33\n",
            "Training pass 34\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri2\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri2/log/analyze_alignments.log\n",
            "125 warnings in exp/tri2/log/align.*.*.log\n",
            "16 warnings in exp/tri2/log/update.*.log\n",
            "4 warnings in exp/tri2/log/lda_acc.*.log\n",
            "50 warnings in exp/tri2/log/init_model.log\n",
            "1 warnings in exp/tri2/log/build_tree.log\n",
            "111 warnings in exp/tri2/log/acc.*.*.log\n",
            "exp/tri2: nj=2 align prob=-48.07 over 5.29h [retry=2.1%, fail=0.2%] states=2072 gauss=15029 tree-impr=5.29 lda-sum=22.84 mllt:impr,logdet=0.97,1.48\n",
            "steps/train_lda_mllt.sh: Done training system with LDA+MLLT features in exp/tri2\n",
            "steps/align_si.sh --nj 2 --cmd run.pl data/train data/lang exp/tri2 exp/tri2_ali\n",
            "steps/align_si.sh: feature type is lda\n",
            "steps/align_si.sh: aligning data in data/train using model from exp/tri2, putting alignments in exp/tri2_ali\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri2_ali\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri2_ali/log/analyze_alignments.log\n",
            "steps/align_si.sh: done aligning data.\n",
            "steps/train_lda_mllt.sh --cmd run.pl 2500 20000 data/train data/lang exp/tri2_ali exp/tri3\n",
            "steps/train_lda_mllt.sh: Accumulating LDA statistics.\n",
            "steps/train_lda_mllt.sh: Accumulating tree stats\n",
            "steps/train_lda_mllt.sh: Getting questions for tree clustering.\n",
            "steps/train_lda_mllt.sh: Building the tree\n",
            "steps/train_lda_mllt.sh: Initializing the model\n",
            "steps/train_lda_mllt.sh: Converting alignments from exp/tri2_ali to use current tree\n",
            "steps/train_lda_mllt.sh: Compiling graphs of transcripts\n",
            "Training pass 1\n",
            "Training pass 2\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 3\n",
            "Training pass 4\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 5\n",
            "Training pass 6\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 7\n",
            "Training pass 8\n",
            "Training pass 9\n",
            "Training pass 10\n",
            "Aligning data\n",
            "Training pass 11\n",
            "Training pass 12\n",
            "steps/train_lda_mllt.sh: Estimating MLLT\n",
            "Training pass 13\n",
            "Training pass 14\n",
            "Training pass 15\n",
            "Training pass 16\n",
            "Training pass 17\n",
            "Training pass 18\n",
            "Training pass 19\n",
            "Training pass 20\n",
            "Aligning data\n",
            "Training pass 21\n",
            "Training pass 22\n",
            "Training pass 23\n",
            "Training pass 24\n",
            "Training pass 25\n",
            "Training pass 26\n",
            "Training pass 27\n",
            "Training pass 28\n",
            "Training pass 29\n",
            "Training pass 30\n",
            "Aligning data\n",
            "Training pass 31\n",
            "Training pass 32\n",
            "Training pass 33\n",
            "Training pass 34\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri3\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri3/log/analyze_alignments.log\n",
            "13 warnings in exp/tri3/log/update.*.log\n",
            "31 warnings in exp/tri3/log/init_model.log\n",
            "102 warnings in exp/tri3/log/acc.*.*.log\n",
            "3 warnings in exp/tri3/log/lda_acc.*.log\n",
            "1 warnings in exp/tri3/log/build_tree.log\n",
            "91 warnings in exp/tri3/log/align.*.*.log\n",
            "exp/tri3: nj=2 align prob=-47.83 over 5.29h [retry=1.3%, fail=0.2%] states=2080 gauss=20029 tree-impr=5.55 lda-sum=24.57 mllt:impr,logdet=1.02,1.66\n",
            "steps/train_lda_mllt.sh: Done training system with LDA+MLLT features in exp/tri3\n",
            "steps/align_si.sh --nj 2 --cmd run.pl data/train data/lang exp/tri3 exp/tri3_ali\n",
            "steps/align_si.sh: feature type is lda\n",
            "steps/align_si.sh: aligning data in data/train using model from exp/tri3, putting alignments in exp/tri3_ali\n",
            "steps/diagnostic/analyze_alignments.sh --cmd run.pl data/lang exp/tri3_ali\n",
            "steps/diagnostic/analyze_alignments.sh: see stats in exp/tri3_ali/log/analyze_alignments.log\n",
            "steps/align_si.sh: done aligning data.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!sed -i 's:--nj 10:--nj 2:g' local/chain/run_tdnn.sh\n",
        "!sed -i 's:steps/nnet3/chain/train.py:steps/nnet3/chain/train.py --use-gpu false:g' local/chain/run_tdnn.sh\n",
        "!cat local/chain/run_tdnn.sh\n",
        "!bash local/chain/run_tdnn.sh"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sWKGX5f-fpKJ",
        "outputId": "26dcf7dc-a08b-46bb-d72d-6c52397c287d"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "#!/bin/bash\n",
            "\n",
            "# Set -e here so that we catch if any executable fails immediately\n",
            "set -euo pipefail\n",
            "\n",
            "# (some of which are also used in this script directly).\n",
            "stage=-1\n",
            "decode_nj=10\n",
            "train_set=train\n",
            "gmm=tri3\n",
            "nnet3_affix=\n",
            "suffix=\n",
            "\n",
            "# The rest are configs specific to this script.  Most of the parameters\n",
            "# are just hardcoded at this level, in the commands below.\n",
            "affix=   # affix for the TDNN directory name\n",
            "tree_affix=\n",
            "train_stage=-10\n",
            "get_egs_stage=-10\n",
            "decode_iter=\n",
            "\n",
            "# training options\n",
            "# training chunk-options\n",
            "chunk_width=140,100,160\n",
            "common_egs_dir=\n",
            "xent_regularize=0.1\n",
            "dropout_schedule='0,0@0.20,0.5@0.50,0'\n",
            "\n",
            "# training options\n",
            "srand=0\n",
            "remove_egs=true\n",
            "\n",
            "# End configuration section.\n",
            "echo \"$0 $@\"  # Print the command line for logging\n",
            "\n",
            ". ./cmd.sh\n",
            ". ./path.sh\n",
            ". ./utils/parse_options.sh\n",
            "\n",
            "# Problem: We have removed the \"train_\" prefix of our training set in\n",
            "# the alignment directory names! Bad!\n",
            "gmm_dir=exp/$gmm\n",
            "ali_dir=exp/${gmm}_ali\n",
            "tree_dir=exp/chain${suffix}/tree${tree_affix:+_$tree_affix}\n",
            "lang=data/lang_chain${suffix}\n",
            "lat_dir=exp/chain${suffix}/${gmm}_${train_set}_lats\n",
            "dir=exp/chain${suffix}/tdnn${affix}\n",
            "train_data_dir=data/${train_set}\n",
            "\n",
            "for f in $gmm_dir/final.mdl $train_data_dir/feats.scp $ali_dir/ali.1.gz; do\n",
            "  [ ! -f $f ] && echo \"$0: expected file $f to exist\" && exit 1\n",
            "done\n",
            "\n",
            "if [ $stage -le 9 ]; then\n",
            "    local/chain/run_ivector_common.sh \\\n",
            "                          --train-set ${train_set} \\\n",
            "                          --gmm ${gmm} \\\n",
            "                          --suffix \"${suffix}\"\n",
            "fi\n",
            "\n",
            "if [ $stage -le 10 ]; then\n",
            "  echo \"$0: creating lang directory $lang with chain-type topology\"\n",
            "  rm -rf $lang\n",
            "  cp -r data/lang $lang\n",
            "  silphonelist=$(cat $lang/phones/silence.csl) \n",
            "  nonsilphonelist=$(cat $lang/phones/nonsilence.csl) \n",
            "  steps/nnet3/chain/gen_topo.py $nonsilphonelist $silphonelist >$lang/topo\n",
            "fi\n",
            "\n",
            "if [ $stage -le 11 ]; then\n",
            "    steps/align_fmllr_lats.sh --nj 20 --cmd \"$train_cmd\" ${train_data_dir} \\\n",
            "         data/lang $gmm_dir $lat_dir\n",
            "fi\n",
            "\n",
            "if [ $stage -le 12 ]; then\n",
            "  steps/nnet3/chain/build_tree.sh \\\n",
            "    --frame-subsampling-factor 3 \\\n",
            "    --context-opts \"--context-width=2 --central-position=1\" \\\n",
            "    --cmd \"$train_cmd\" 2500 ${train_data_dir} \\\n",
            "    $lang $ali_dir $tree_dir\n",
            "fi\n",
            "\n",
            "if [ $stage -le 13 ]; then\n",
            "  echo \"$0: creating neural net configs using the xconfig parser\";\n",
            "\n",
            "  num_targets=$(tree-info $tree_dir/tree | grep num-pdfs | awk '{print $2}')\n",
            "  learning_rate_factor=$(echo \"print (0.5/$xent_regularize)\" | python)\n",
            "\n",
            "  affine_opts=\"l2-regularize=0.008 dropout-proportion=0.0 dropout-per-dim=true dropout-per-dim-continuous=true\"\n",
            "  tdnnf_opts=\"l2-regularize=0.008 dropout-proportion=0.0 bypass-scale=0.75\"\n",
            "  linear_opts=\"l2-regularize=0.008 orthonormal-constraint=-1.0\"\n",
            "  prefinal_opts=\"l2-regularize=0.008\"\n",
            "  output_opts=\"l2-regularize=0.002\"\n",
            "\n",
            "  mkdir -p $dir/configs\n",
            "  cat <<EOF > $dir/configs/network.xconfig\n",
            "\n",
            "  input dim=40 name=ivector\n",
            "  input dim=40 name=input\n",
            "\n",
            "  idct-layer name=idct input=input dim=40 cepstral-lifter=22 affine-transform-file=$dir/configs/idct.mat\n",
            "  batchnorm-component name=batchnorm0 input=idct\n",
            "  spec-augment-layer name=spec-augment freq-max-proportion=0.5 time-zeroed-proportion=0.2 time-mask-max-frames=20\n",
            "  delta-layer name=delta input=spec-augment\n",
            "\n",
            "  no-op-component name=input2 input=Append(delta, ReplaceIndex(ivector, t, 0))\n",
            "\n",
            "  # the first splicing is moved before the lda layer, so no splicing here\n",
            "  relu-batchnorm-dropout-layer name=tdnn1 $affine_opts dim=512 input=input2\n",
            "  tdnnf-layer name=tdnnf2 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=1\n",
            "  tdnnf-layer name=tdnnf3 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=1\n",
            "  tdnnf-layer name=tdnnf4 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=1\n",
            "  tdnnf-layer name=tdnnf5 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=0\n",
            "  tdnnf-layer name=tdnnf6 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf7 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf8 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf9 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf10 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf11 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  tdnnf-layer name=tdnnf12 $tdnnf_opts dim=512 bottleneck-dim=96 time-stride=3\n",
            "  linear-component name=prefinal-l dim=192 $linear_opts\n",
            "\n",
            "  ## adding the layers for chain branch\n",
            "  prefinal-layer name=prefinal-chain input=prefinal-l $prefinal_opts small-dim=192 big-dim=512\n",
            "  output-layer name=output include-log-softmax=false dim=$num_targets $output_opts\n",
            "\n",
            "  # adding the layers for xent branch\n",
            "  prefinal-layer name=prefinal-xent input=prefinal-l $prefinal_opts small-dim=192 big-dim=512\n",
            "  output-layer name=output-xent dim=$num_targets learning-rate-factor=$learning_rate_factor $output_opts\n",
            "\n",
            "EOF\n",
            "  steps/nnet3/xconfig_to_configs.py --xconfig-file $dir/configs/network.xconfig --config-dir $dir/configs/\n",
            "fi\n",
            "\n",
            "if [ $stage -le 14 ]; then\n",
            "  steps/nnet3/chain/train.py --use-gpu false --stage $train_stage \\\n",
            "    --cmd \"$cuda_cmd\" \\\n",
            "    --feat.online-ivector-dir exp/chain${suffix}/ivectors_${train_set} \\\n",
            "    --feat.cmvn-opts \"--norm-means=false --norm-vars=false\" \\\n",
            "    --chain.xent-regularize $xent_regularize \\\n",
            "    --chain.leaky-hmm-coefficient 0.1 \\\n",
            "    --chain.l2-regularize 0.0 \\\n",
            "    --chain.apply-deriv-weights false \\\n",
            "    --chain.lm-opts=\"--num-extra-lm-states=2000\" \\\n",
            "    --egs.cmd \"$get_egs_cmd\" \\\n",
            "    --egs.dir \"$common_egs_dir\" \\\n",
            "    --egs.stage $get_egs_stage \\\n",
            "    --egs.opts \"--frames-overlap-per-eg 0 --constrained false\" \\\n",
            "    --egs.chunk-width $chunk_width \\\n",
            "    --trainer.dropout-schedule $dropout_schedule \\\n",
            "    --trainer.add-option=\"--optimization.memory-compression-level=2\" \\\n",
            "    --trainer.num-chunk-per-minibatch 64 \\\n",
            "    --trainer.frames-per-iter 2500000 \\\n",
            "    --trainer.num-epochs 20 \\\n",
            "    --trainer.optimization.num-jobs-initial 1 \\\n",
            "    --trainer.optimization.num-jobs-final 1 \\\n",
            "    --trainer.optimization.initial-effective-lrate 0.001 \\\n",
            "    --trainer.optimization.final-effective-lrate 0.0001 \\\n",
            "    --trainer.max-param-change 2.0 \\\n",
            "    --cleanup.remove-egs $remove_egs \\\n",
            "    --feat-dir $train_data_dir \\\n",
            "    --tree-dir $tree_dir \\\n",
            "    --lat-dir $lat_dir \\\n",
            "    --dir $dir  || exit 1;\n",
            "fi\n",
            "local/chain/run_tdnn.sh \n",
            "local/chain/run_ivector_common.sh: computing a subset of data to train the diagonal UBM.\n",
            "utils/data/subset_data_dir.sh: reducing #utt from 1519 to 379\n",
            "local/chain/run_ivector_common.sh: computing a PCA transform from the data.\n",
            "steps/online/nnet2/get_pca_transform.sh --cmd run.pl --splice-opts --left-context=3 --right-context=3 --max-utts 10000 --subsample 2 exp/chain/diag_ubm/train_subset exp/chain/pca_transform\n",
            "Done estimating PCA transform in exp/chain/pca_transform\n",
            "local/chain/run_ivector_common.sh: training the diagonal UBM.\n",
            "steps/online/nnet2/train_diag_ubm.sh --cmd run.pl --nj 10 --num-frames 700000 --num-threads 8 exp/chain/diag_ubm/train_subset 512 exp/chain/pca_transform exp/chain/diag_ubm\n",
            "steps/online/nnet2/train_diag_ubm.sh: Directory exp/chain/diag_ubm already exists. Backing up diagonal UBM in exp/chain/diag_ubm/backup.WXg\n",
            "steps/online/nnet2/train_diag_ubm.sh: initializing model from E-M in memory, \n",
            "steps/online/nnet2/train_diag_ubm.sh: starting from 256 Gaussians, reaching 512;\n",
            "steps/online/nnet2/train_diag_ubm.sh: for 20 iterations, using at most 700000 frames of data\n",
            "Getting Gaussian-selection info\n",
            "steps/online/nnet2/train_diag_ubm.sh: will train for 4 iterations, in parallel over\n",
            "steps/online/nnet2/train_diag_ubm.sh: 10 machines, parallelized with 'run.pl'\n",
            "steps/online/nnet2/train_diag_ubm.sh: Training pass 0\n",
            "steps/online/nnet2/train_diag_ubm.sh: Training pass 1\n",
            "steps/online/nnet2/train_diag_ubm.sh: Training pass 2\n",
            "steps/online/nnet2/train_diag_ubm.sh: Training pass 3\n",
            "local/chain/run_ivector_common.sh: training the iVector extractor\n",
            "steps/online/nnet2/train_ivector_extractor.sh --cmd run.pl --nj 2 --ivector-dim 40 data/train exp/chain/diag_ubm exp/chain/extractor\n",
            "steps/online/nnet2/train_ivector_extractor.sh: Directory exp/chain/extractor already exists. Backing up iVector extractor in exp/chain/extractor/backup.YGm\n",
            "steps/online/nnet2/train_ivector_extractor.sh: doing Gaussian selection and posterior computation\n",
            "Accumulating stats (pass 0)\n",
            "Summing accs (pass 0)\n",
            "Updating model (pass 0)\n",
            "Accumulating stats (pass 1)\n",
            "Summing accs (pass 1)\n",
            "Updating model (pass 1)\n",
            "Accumulating stats (pass 2)\n",
            "Summing accs (pass 2)\n",
            "Updating model (pass 2)\n",
            "Accumulating stats (pass 3)\n",
            "Summing accs (pass 3)\n",
            "Updating model (pass 3)\n",
            "Accumulating stats (pass 4)\n",
            "Summing accs (pass 4)\n",
            "Updating model (pass 4)\n",
            "Accumulating stats (pass 5)\n",
            "Summing accs (pass 5)\n",
            "Updating model (pass 5)\n",
            "Accumulating stats (pass 6)\n",
            "Summing accs (pass 6)\n",
            "Updating model (pass 6)\n",
            "Accumulating stats (pass 7)\n",
            "Summing accs (pass 7)\n",
            "Updating model (pass 7)\n",
            "Accumulating stats (pass 8)\n",
            "Summing accs (pass 8)\n",
            "Updating model (pass 8)\n",
            "Accumulating stats (pass 9)\n",
            "Summing accs (pass 9)\n",
            "Updating model (pass 9)\n",
            "utils/data/modify_speaker_info.sh: copied data from data/train to exp/chain/ivectors_train/train_max2, number of speakers changed from 29 to 768\n",
            "utils/validate_data_dir.sh: Successfully validated data-directory exp/chain/ivectors_train/train_max2\n",
            "steps/online/nnet2/extract_ivectors_online.sh --cmd run.pl --nj 10 exp/chain/ivectors_train/train_max2 exp/chain/extractor exp/chain/ivectors_train\n",
            "steps/online/nnet2/extract_ivectors_online.sh: extracting iVectors\n",
            "steps/online/nnet2/extract_ivectors_online.sh: combining iVectors across jobs\n",
            "steps/online/nnet2/extract_ivectors_online.sh: done extracting (online) iVectors to exp/chain/ivectors_train using the extractor in exp/chain/extractor.\n",
            "local/chain/run_tdnn.sh: creating lang directory data/lang_chain with chain-type topology\n",
            "steps/align_fmllr_lats.sh --nj 20 --cmd run.pl data/train data/lang exp/tri3 exp/chain/tri3_train_lats\n",
            "steps/align_fmllr_lats.sh: feature type is lda\n",
            "steps/align_fmllr_lats.sh: compiling training graphs\n",
            "steps/align_fmllr_lats.sh: aligning data in data/train using exp/tri3/final.mdl and speaker-independent features.\n",
            "steps/align_fmllr_lats.sh: computing fMLLR transforms\n",
            "steps/align_fmllr_lats.sh: generating lattices containing alternate pronunciations.\n",
            "steps/align_fmllr_lats.sh: done generating lattices from training transcripts.\n",
            "44 warnings in exp/chain/tri3_train_lats/log/align_pass1.*.log\n",
            "20 warnings in exp/chain/tri3_train_lats/log/generate_lattices.*.log\n",
            "3 warnings in exp/chain/tri3_train_lats/log/fmllr.*.log\n",
            "steps/nnet3/chain/build_tree.sh --frame-subsampling-factor 3 --context-opts --context-width=2 --central-position=1 --cmd run.pl 2500 data/train data/lang_chain exp/tri3_ali exp/chain/tree\n",
            "steps/nnet3/chain/build_tree.sh: feature type is lda\n",
            "steps/nnet3/chain/build_tree.sh: Initializing monophone model (for alignment conversion, in case topology changed)\n",
            "steps/nnet3/chain/build_tree.sh: Accumulating tree stats\n",
            "steps/nnet3/chain/build_tree.sh: Getting questions for tree clustering.\n",
            "steps/nnet3/chain/build_tree.sh: Building the tree\n",
            "steps/nnet3/chain/build_tree.sh: Initializing the model\n",
            "steps/nnet3/chain/build_tree.sh: Converting alignments from exp/tri3_ali to use current tree\n",
            "steps/nnet3/chain/build_tree.sh: Done building tree\n",
            "local/chain/run_tdnn.sh: creating neural net configs using the xconfig parser\n",
            "tree-info exp/chain/tree/tree \n",
            "steps/nnet3/xconfig_to_configs.py --xconfig-file exp/chain/tdnn/configs/network.xconfig --config-dir exp/chain/tdnn/configs/\n",
            "nnet3-init exp/chain/tdnn/configs//ref.config exp/chain/tdnn/configs//ref.raw \n",
            "LOG (nnet3-init[5.5.1046~1-76cd5]:main():nnet3-init.cc:80) Initialized raw neural net and wrote it to exp/chain/tdnn/configs//ref.raw\n",
            "nnet3-info exp/chain/tdnn/configs//ref.raw \n",
            "nnet3-init exp/chain/tdnn/configs//ref.config exp/chain/tdnn/configs//ref.raw \n",
            "LOG (nnet3-init[5.5.1046~1-76cd5]:main():nnet3-init.cc:80) Initialized raw neural net and wrote it to exp/chain/tdnn/configs//ref.raw\n",
            "nnet3-info exp/chain/tdnn/configs//ref.raw \n",
            "2022-08-17 13:33:35,936 [steps/nnet3/chain/train.py:35 - <module> - INFO ] Starting chain model trainer (train.py)\n",
            "steps/nnet3/chain/train.py --use-gpu false --stage -10 --cmd run.pl --feat.online-ivector-dir exp/chain/ivectors_train --feat.cmvn-opts --norm-means=false --norm-vars=false --chain.xent-regularize 0.1 --chain.leaky-hmm-coefficient 0.1 --chain.l2-regularize 0.0 --chain.apply-deriv-weights false --chain.lm-opts=--num-extra-lm-states=2000 --egs.cmd run.pl --egs.dir  --egs.stage -10 --egs.opts --frames-overlap-per-eg 0 --constrained false --egs.chunk-width 140,100,160 --trainer.dropout-schedule 0,0@0.20,0.5@0.50,0 --trainer.add-option=--optimization.memory-compression-level=2 --trainer.num-chunk-per-minibatch 64 --trainer.frames-per-iter 2500000 --trainer.num-epochs 20 --trainer.optimization.num-jobs-initial 1 --trainer.optimization.num-jobs-final 1 --trainer.optimization.initial-effective-lrate 0.001 --trainer.optimization.final-effective-lrate 0.0001 --trainer.max-param-change 2.0 --cleanup.remove-egs true --feat-dir data/train --tree-dir exp/chain/tree --lat-dir exp/chain/tri3_train_lats --dir exp/chain/tdnn\n",
            "['steps/nnet3/chain/train.py', '--use-gpu', 'false', '--stage', '-10', '--cmd', 'run.pl', '--feat.online-ivector-dir', 'exp/chain/ivectors_train', '--feat.cmvn-opts', '--norm-means=false --norm-vars=false', '--chain.xent-regularize', '0.1', '--chain.leaky-hmm-coefficient', '0.1', '--chain.l2-regularize', '0.0', '--chain.apply-deriv-weights', 'false', '--chain.lm-opts=--num-extra-lm-states=2000', '--egs.cmd', 'run.pl', '--egs.dir', '', '--egs.stage', '-10', '--egs.opts', '--frames-overlap-per-eg 0 --constrained false', '--egs.chunk-width', '140,100,160', '--trainer.dropout-schedule', '0,0@0.20,0.5@0.50,0', '--trainer.add-option=--optimization.memory-compression-level=2', '--trainer.num-chunk-per-minibatch', '64', '--trainer.frames-per-iter', '2500000', '--trainer.num-epochs', '20', '--trainer.optimization.num-jobs-initial', '1', '--trainer.optimization.num-jobs-final', '1', '--trainer.optimization.initial-effective-lrate', '0.001', '--trainer.optimization.final-effective-lrate', '0.0001', '--trainer.max-param-change', '2.0', '--cleanup.remove-egs', 'true', '--feat-dir', 'data/train', '--tree-dir', 'exp/chain/tree', '--lat-dir', 'exp/chain/tri3_train_lats', '--dir', 'exp/chain/tdnn']\n",
            "2022-08-17 13:33:35,938 [steps/nnet3/chain/train.py:255 - process_args - WARNING ] Without using a GPU this will be very slow. nnet3 does not yet support multiple threads.\n",
            "2022-08-17 13:33:35,939 [steps/nnet3/chain/train.py:281 - train - INFO ] Arguments for the experiment\n",
            "{'alignment_subsampling_factor': 3,\n",
            " 'apply_deriv_weights': False,\n",
            " 'backstitch_training_interval': 1,\n",
            " 'backstitch_training_scale': 0.0,\n",
            " 'chunk_left_context': 0,\n",
            " 'chunk_left_context_initial': -1,\n",
            " 'chunk_right_context': 0,\n",
            " 'chunk_right_context_final': -1,\n",
            " 'chunk_width': '140,100,160',\n",
            " 'cleanup': True,\n",
            " 'cmvn_opts': '--norm-means=false --norm-vars=false',\n",
            " 'combine_sum_to_one_penalty': 0.0,\n",
            " 'command': 'run.pl',\n",
            " 'compute_per_dim_accuracy': False,\n",
            " 'deriv_truncate_margin': None,\n",
            " 'dir': 'exp/chain/tdnn',\n",
            " 'do_final_combination': True,\n",
            " 'dropout_schedule': '0,0@0.20,0.5@0.50,0',\n",
            " 'egs_command': 'run.pl',\n",
            " 'egs_dir': None,\n",
            " 'egs_nj': 0,\n",
            " 'egs_opts': '--frames-overlap-per-eg 0 --constrained false',\n",
            " 'egs_stage': -10,\n",
            " 'email': None,\n",
            " 'exit_stage': None,\n",
            " 'feat_dir': 'data/train',\n",
            " 'final_effective_lrate': 0.0001,\n",
            " 'frame_subsampling_factor': 3,\n",
            " 'frames_per_iter': 2500000,\n",
            " 'initial_effective_lrate': 0.001,\n",
            " 'input_model': None,\n",
            " 'l2_regularize': 0.0,\n",
            " 'lat_dir': 'exp/chain/tri3_train_lats',\n",
            " 'leaky_hmm_coefficient': 0.1,\n",
            " 'left_deriv_truncate': None,\n",
            " 'left_tolerance': 5,\n",
            " 'lm_opts': '--num-extra-lm-states=2000',\n",
            " 'max_lda_jobs': 10,\n",
            " 'max_models_combine': 20,\n",
            " 'max_objective_evaluations': 30,\n",
            " 'max_param_change': 2.0,\n",
            " 'momentum': 0.0,\n",
            " 'num_chunk_per_minibatch': '64',\n",
            " 'num_epochs': 20.0,\n",
            " 'num_jobs_final': 1,\n",
            " 'num_jobs_initial': 1,\n",
            " 'num_jobs_step': 1,\n",
            " 'online_ivector_dir': 'exp/chain/ivectors_train',\n",
            " 'preserve_model_interval': 100,\n",
            " 'presoftmax_prior_scale_power': -0.25,\n",
            " 'proportional_shrink': 0.0,\n",
            " 'rand_prune': 4.0,\n",
            " 'remove_egs': True,\n",
            " 'reporting_interval': 0.1,\n",
            " 'right_tolerance': 5,\n",
            " 'samples_per_iter': 400000,\n",
            " 'shrink_saturation_threshold': 0.4,\n",
            " 'shrink_value': 1.0,\n",
            " 'shuffle_buffer_size': 5000,\n",
            " 'srand': 0,\n",
            " 'stage': -10,\n",
            " 'train_opts': ['--optimization.memory-compression-level=2'],\n",
            " 'tree_dir': 'exp/chain/tree',\n",
            " 'use_gpu': 'no',\n",
            " 'xent_regularize': 0.1}\n",
            "2022-08-17 13:33:35,976 [steps/nnet3/chain/train.py:338 - train - INFO ] Creating phone language-model\n",
            "2022-08-17 13:33:36,333 [steps/nnet3/chain/train.py:343 - train - INFO ] Creating denominator FST\n",
            "copy-transition-model exp/chain/tree/final.mdl exp/chain/tdnn/0.trans_mdl \n",
            "LOG (copy-transition-model[5.5.1046~1-76cd5]:main():copy-transition-model.cc:62) Copied transition model.\n",
            "2022-08-17 13:33:36,951 [steps/nnet3/chain/train.py:379 - train - INFO ] Generating egs\n",
            "steps/nnet3/chain/get_egs.sh --frames-overlap-per-eg 0 --constrained false --cmd run.pl --cmvn-opts --norm-means=false --norm-vars=false --online-ivector-dir exp/chain/ivectors_train --left-context 27 --right-context 27 --left-context-initial -1 --right-context-final -1 --left-tolerance 5 --right-tolerance 5 --frame-subsampling-factor 3 --alignment-subsampling-factor 3 --stage -10 --frames-per-iter 2500000 --frames-per-eg 140,100,160 --srand 0 data/train exp/chain/tdnn exp/chain/tri3_train_lats exp/chain/tdnn/egs\n",
            "steps/nnet3/chain/get_egs.sh: Holding out 300 utterances in validation set and 300 in training diagnostic set, out of total 1519.\n",
            "steps/nnet3/chain/get_egs.sh: creating egs.  To ensure they are not deleted later you can do:  touch exp/chain/tdnn/egs/.nodelete\n",
            "steps/nnet3/chain/get_egs.sh: feature type is raw, with 'apply-cmvn'\n",
            "tree-info exp/chain/tdnn/tree \n",
            "feat-to-dim scp:exp/chain/ivectors_train/ivector_online.scp - \n",
            "steps/nnet3/chain/get_egs.sh: working out number of frames of training data\n",
            "steps/nnet3/chain/get_egs.sh: working out feature dim\n",
            "steps/nnet3/chain/get_egs.sh: creating 1 archives, each with 11949 egs, with\n",
            "steps/nnet3/chain/get_egs.sh:   140,100,160 labels per example, and (left,right) context = (27,27)\n",
            "steps/nnet3/chain/get_egs.sh: Getting validation and training subset examples in background.\n",
            "steps/nnet3/chain/get_egs.sh: Generating training examples on disk\n",
            "steps/nnet3/chain/get_egs.sh: recombining and shuffling order of archives on disk\n",
            "steps/nnet3/chain/get_egs.sh: Getting subsets of validation examples for diagnostics and combination.\n",
            "steps/nnet3/chain/get_egs.sh: Removing temporary archives, alignments and lattices\n",
            "steps/nnet3/chain/get_egs.sh: Finished preparing training examples\n",
            "2022-08-17 13:34:13,249 [steps/nnet3/chain/train.py:428 - train - INFO ] Copying the properties from exp/chain/tdnn/egs to exp/chain/tdnn\n",
            "2022-08-17 13:34:13,249 [steps/nnet3/chain/train.py:451 - train - INFO ] Preparing the initial acoustic model.\n",
            "2022-08-17 13:34:13,511 [steps/nnet3/chain/train.py:485 - train - INFO ] Training will run for 20.0 epochs = 60 iterations\n",
            "2022-08-17 13:34:13,511 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 0/59   Jobs: 1   Epoch: 0.00/20.0 (0.0% complete)   lr: 0.001000   \n",
            "2022-08-17 13:45:06,298 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 1/59   Jobs: 1   Epoch: 0.33/20.0 (1.7% complete)   lr: 0.000962   \n",
            "2022-08-17 13:57:11,651 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 2/59   Jobs: 1   Epoch: 0.67/20.0 (3.3% complete)   lr: 0.000926   \n",
            "2022-08-17 14:09:18,884 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 3/59   Jobs: 1   Epoch: 1.00/20.0 (5.0% complete)   lr: 0.000891   \n",
            "2022-08-17 14:21:18,325 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 4/59   Jobs: 1   Epoch: 1.33/20.0 (6.7% complete)   lr: 0.000858   \n",
            "2022-08-17 14:33:01,155 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 5/59   Jobs: 1   Epoch: 1.67/20.0 (8.3% complete)   lr: 0.000825   \n",
            "2022-08-17 14:45:02,351 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 6/59   Jobs: 1   Epoch: 2.00/20.0 (10.0% complete)   lr: 0.000794   \n",
            "2022-08-17 14:57:33,705 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 7/59   Jobs: 1   Epoch: 2.33/20.0 (11.7% complete)   lr: 0.000764   \n",
            "2022-08-17 15:10:01,021 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 8/59   Jobs: 1   Epoch: 2.67/20.0 (13.3% complete)   lr: 0.000736   \n",
            "2022-08-17 15:22:10,748 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 9/59   Jobs: 1   Epoch: 3.00/20.0 (15.0% complete)   lr: 0.000708   \n",
            "2022-08-17 15:34:09,008 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 10/59   Jobs: 1   Epoch: 3.33/20.0 (16.7% complete)   lr: 0.000681   \n",
            "2022-08-17 15:45:51,448 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 11/59   Jobs: 1   Epoch: 3.67/20.0 (18.3% complete)   lr: 0.000656   \n",
            "2022-08-17 15:57:34,728 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 12/59   Jobs: 1   Epoch: 4.00/20.0 (20.0% complete)   lr: 0.000631   \n",
            "2022-08-17 16:09:19,257 [steps/nnet3/chain/train.py:529 - train - INFO ] Iter: 13/59   Jobs: 1   Epoch: 4.33/20.0 (21.7% complete)   lr: 0.000607   \n",
            "2022-08-17 16:15:40,558 [steps/libs/common.py:236 - background_command_waiter - ERROR ] Command exited with status -2: run.pl  exp/chain/tdnn/log/train.13.1.log                     nnet3-chain-train --use-gpu=no                      --apply-deriv-weights=False                     --l2-regularize=0.0 --leaky-hmm-coefficient=0.1                     --read-cache=exp/chain/tdnn/cache.13 --write-cache=exp/chain/tdnn/cache.14  --xent-regularize=0.1                                          --print-interval=10 --momentum=0.0                     --max-param-change=2.0                     --backstitch-training-scale=0.0                     --backstitch-training-interval=1                     --l2-regularize-factor=1.0 --optimization.memory-compression-level=2                     --srand=13                     \"nnet3-am-copy --raw=true --learning-rate=0.000607202195691 --scale=1.0 exp/chain/tdnn/13.mdl - |nnet3-copy --edits='set-dropout-proportion name=* proportion=0.0277777777778' - - |\" exp/chain/tdnn/den.fst                     \"ark,bg:nnet3-chain-copy-egs                          --frame-shift=2                         ark:exp/chain/tdnn/egs/cegs.1.ark ark:- |                         nnet3-chain-shuffle-egs --buffer-size=5000                         --srand=13 ark:- ark:- | nnet3-chain-merge-egs                         --minibatch-size=64 ark:- ark:- |\"                     exp/chain/tdnn/14.1.raw\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!cp exp/chain/tdnn/13.mdl exp/chain/tdnn/final.mdl"
      ],
      "metadata": {
        "id": "_6cOADJBluSm"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!bash run.sh --stage 5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "La4qqC-kl9lf",
        "outputId": "3d0cc930-43a2-4ec9-81b9-8436fed8669f"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Converting 'data/local/lm/lm_tgsmall.arpa.gz' to FST\n",
            "arpa2fst --disambig-symbol=#0 --read-symbol-table=data/lang_test/words.txt - data/lang_test/G.fst \n",
            "LOG (arpa2fst[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:94) Reading \\data\\ section.\n",
            "LOG (arpa2fst[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\1-grams: section.\n",
            "LOG (arpa2fst[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\2-grams: section.\n",
            "LOG (arpa2fst[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\3-grams: section.\n",
            "LOG (arpa2fst[5.5.1046~1-76cd5]:RemoveRedundantStates():arpa-lm-compiler.cc:359) Reduced num-states from 1183418 to 249533\n",
            "fstisstochastic data/lang_test/G.fst \n",
            "9.90926e-06 -0.29805\n",
            "Succeeded in formatting LM: 'data/local/lm/lm_tgsmall.arpa.gz'\n",
            "tree-info exp/chain/tdnn/tree \n",
            "tree-info exp/chain/tdnn/tree \n",
            "fstdeterminizestar --use-log=true \n",
            "fsttablecompose data/lang_test/L_disambig.fst data/lang_test/G.fst \n",
            "fstpushspecial \n",
            "fstminimizeencoded \n",
            "fstisstochastic data/lang_test/tmp/LG.fst \n",
            "-0.0577829 -0.0586653\n",
            "[info]: LG not stochastic.\n",
            "fstcomposecontext --context-size=2 --central-position=1 --read-disambig-syms=data/lang_test/phones/disambig.int --write-disambig-syms=data/lang_test/tmp/disambig_ilabels_2_1.int data/lang_test/tmp/ilabels_2_1.339337 data/lang_test/tmp/LG.fst \n",
            "fstisstochastic data/lang_test/tmp/CLG_2_1.fst \n",
            "-0.0577829 -0.0586653\n",
            "[info]: CLG not stochastic.\n",
            "make-h-transducer --disambig-syms-out=exp/chain/tdnn/graph/disambig_tid.int --transition-scale=1.0 data/lang_test/tmp/ilabels_2_1 exp/chain/tdnn/tree exp/chain/tdnn/final.mdl \n",
            "fsttablecompose exp/chain/tdnn/graph/Ha.fst data/lang_test/tmp/CLG_2_1.fst \n",
            "fstdeterminizestar --use-log=true \n",
            "fstrmepslocal \n",
            "fstrmsymbols exp/chain/tdnn/graph/disambig_tid.int \n",
            "fstminimizeencoded \n",
            "fstisstochastic exp/chain/tdnn/graph/HCLGa.fst \n",
            "-0.019117 -0.213417\n",
            "HCLGa is not stochastic\n",
            "add-self-loops --self-loop-scale=1.0 --reorder=true exp/chain/tdnn/final.mdl exp/chain/tdnn/graph/HCLGa.fst \n",
            "fstisstochastic exp/chain/tdnn/graph/HCLG.fst \n",
            "1.90465e-09 -0.146711\n",
            "[info]: final HCLG is not stochastic.\n",
            "arpa-to-const-arpa --bos-symbol=200004 --eos-symbol=200005 --unk-symbol=2 'gunzip -c data/local/lm/lm_tgmed.arpa.gz | utils/map_arpa_lm.pl data/lang_test_rescore/words.txt|' data/lang_test_rescore/G.carpa \n",
            "LOG (arpa-to-const-arpa[5.5.1046~1-76cd5]:BuildConstArpaLm():const-arpa-lm.cc:1078) Reading gunzip -c data/local/lm/lm_tgmed.arpa.gz | utils/map_arpa_lm.pl data/lang_test_rescore/words.txt|\n",
            "utils/map_arpa_lm.pl: Processing \"\\data\\\"\n",
            "utils/map_arpa_lm.pl: Processing \"\\1-grams:\\\"\n",
            "LOG (arpa-to-const-arpa[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:94) Reading \\data\\ section.\n",
            "LOG (arpa-to-const-arpa[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\1-grams: section.\n",
            "utils/map_arpa_lm.pl: Processing \"\\2-grams:\\\"\n",
            "LOG (arpa-to-const-arpa[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\2-grams: section.\n",
            "utils/map_arpa_lm.pl: Processing \"\\3-grams:\\\"\n",
            "LOG (arpa-to-const-arpa[5.5.1046~1-76cd5]:Read():arpa-file-parser.cc:149) Reading \\3-grams: section.\n",
            "steps/make_mfcc.sh --cmd run.pl --nj 2 data/test exp/make_mfcc/test\n",
            "steps/make_mfcc.sh: moving data/test/feats.scp to data/test/.backup\n",
            "utils/validate_data_dir.sh: Successfully validated data-directory data/test\n",
            "steps/make_mfcc.sh: [info]: no segments file exists: assuming wav.scp indexed by utterance.\n",
            "steps/make_mfcc.sh: Succeeded creating MFCC features for test\n",
            "steps/compute_cmvn_stats.sh data/test exp/make_mfcc/test\n",
            "Succeeded creating CMVN stats for test\n",
            "steps/online/nnet2/extract_ivectors_online.sh --nj 2 data/test exp/chain/extractor exp/chain/ivectors_test\n",
            "steps/online/nnet2/extract_ivectors_online.sh: extracting iVectors\n",
            "steps/online/nnet2/extract_ivectors_online.sh: combining iVectors across jobs\n",
            "steps/online/nnet2/extract_ivectors_online.sh: done extracting (online) iVectors to exp/chain/ivectors_test using the extractor in exp/chain/extractor.\n",
            "steps/nnet3/decode.sh --cmd run.pl --num-threads 10 --nj 1 --beam 13.0 --max-active 7000 --lattice-beam 4.0 --online-ivector-dir exp/chain/ivectors_test --acwt 1.0 --post-decode-acwt 10.0 exp/chain/tdnn/graph data/test exp/chain/tdnn/decode_test\n",
            "steps/nnet3/decode.sh: feature type is raw\n",
            "steps/diagnostic/analyze_lats.sh --cmd run.pl --iter final exp/chain/tdnn/graph exp/chain/tdnn/decode_test\n",
            "steps/diagnostic/analyze_lats.sh: see stats in exp/chain/tdnn/decode_test/log/analyze_alignments.log\n",
            "Overall, lattice depth (10,50,90-percentile)=(1,3,17) and mean=6.9\n",
            "steps/diagnostic/analyze_lats.sh: see stats in exp/chain/tdnn/decode_test/log/analyze_lattice_depth_stats.log\n",
            "score best paths\n",
            "local/score.sh --cmd run.pl data/test exp/chain/tdnn/graph exp/chain/tdnn/decode_test\n",
            "local/score.sh: scoring with word insertion penalty=0.0\n",
            "score confidence and timing with sclite\n",
            "Decoding done.\n",
            "steps/lmrescore_const_arpa.sh data/lang_test data/lang_test_rescore data/test exp/chain/tdnn/decode_test exp/chain/tdnn/decode_test_rescore\n",
            "local/score.sh --cmd run.pl data/test data/lang_test_rescore exp/chain/tdnn/decode_test_rescore\n",
            "local/score.sh: scoring with word insertion penalty=0.0\n",
            "%WER 22.68 [ 4568 / 20138, 254 ins, 945 del, 3369 sub ] exp/chain/tdnn/decode_test/wer_11_0.0\n",
            "%WER 20.24 [ 4076 / 20138, 263 ins, 771 del, 3042 sub ] exp/chain/tdnn/decode_test_rescore/wer_11_0.0\n"
          ]
        }
      ]
    }
  ]
}